Communications of the ACM
Computational methods for rough classification and discovery
Journal of the American Society for Information Science - Special issue: knowledge discovery and data mining
Rough computational methods for information systems
Artificial Intelligence
Uncertainly measures of rough set prediction
Artificial Intelligence
Information-theoretic measures of uncertainty for rough sets and rough relational databases
Information Sciences: an International Journal
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Data mining in incomplete information systems from rough set perspective
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Uncertainty Measures of Roughness of Knowledge and Rough Sets in Ordered Information Systems
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Uncertainty Measure of Covering Generated Rough Set
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Measures for evaluating the decision performance of a decision table in rough set theory
Information Sciences: an International Journal
A weighted rough set based method developed for class imbalance learning
Information Sciences: an International Journal
Attribute reduction based on evidence theory in incomplete decision systems
Information Sciences: an International Journal
Converse approximation and rule extraction from decision tables in rough set theory
Computers & Mathematics with Applications
On the evaluation of the decision performance of an incomplete decision table
Data & Knowledge Engineering
Consistency measure, inclusion degree and fuzzy measure in decision tables
Fuzzy Sets and Systems
A comparative study on rough set based class imbalance learning
Knowledge-Based Systems
Knowledge structure, knowledge granulation and knowledge distance in a knowledge base
International Journal of Approximate Reasoning
Fuzzy-rough attribute reduction via mutual information with an application to cancer classification
Computers & Mathematics with Applications
A Time-Reduction Strategy to Feature Selection in Rough Set Theory
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
Research on rough set theory and applications in China
Transactions on rough sets VIII
Difference similitude method in knowledge reduction
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Combination entropy and combination granulation in incomplete information system
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Distance: A more comprehensible perspective for measures in rough set theory
Knowledge-Based Systems
Axiomatic approach of knowledge granulation in information system
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
An efficient rough feature selection algorithm with a multi-granulation view
International Journal of Approximate Reasoning
An Improved Axiomatic Definition of Information Granulation
Fundamenta Informaticae
Evaluation of the decision performance of the decision rule set from an ordered decision table
Knowledge-Based Systems
Feature selection using rough entropy-based uncertainty measures in incomplete decision systems
Knowledge-Based Systems
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
Multigranulation rough sets: From partition to covering
Information Sciences: an International Journal
Quick attribute reduction in inconsistent decision tables
Information Sciences: an International Journal
A fast feature selection approach based on rough set boundary regions
Pattern Recognition Letters
Updating attribute reduction in incomplete decision systems with the variation of attribute set
International Journal of Approximate Reasoning
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Rough set theory is emerging as a powerful tool for reasoning about data, knowledge reduction is one of the important topics in the research on rough set theory. It has been proven that finding the minimal reduct of an information system is a NP-hard problem, so is finding the minimal reduct of an incomplete information system. Main reason of causing NP-hard is combination problem of attributes. In this paper, knowledge reduction is defined from the view of information, a heuristic algorithm based on rough entropy for knowledge reduction is proposed in incomplete information systems, the time complexity of this algorithm is O(|A|2|U|). An illustrative example is provided that shows the application potential of the algorithm.